Dictionary type data compression method is well known in the art of electronic data compression and are also commonly referred to as a "codebook" or a "macro coding" approach. The various coding schemes in the Ziv-Lempel CLZ") family of data compression techniques are all examples of the dictionary type of data coding method. FIGS. 1 and 2 illustrates two well known LZ family of data compression techniques. FIG. 1 is an example of an LZ-1 compression method using a history buffer 11 to compress an input data stream. A typical LZ-1 data compression method processes an input data stream 10 to generate a compressed data stream 20 by comparing current literal string 13 from input data stream 10 to data in a history buffer 11. If a corresponding data string 12 is located in history buffer 11, a pointer and length (p.sub.o, l.sub.o) 24 is then encoded into output data buffer 20, wherein p.sub.o compounds to offset 15, associated with the memory location of matching data string 12, and l.sub.o corresponds to a data length 16. Pointer (p.sub.o, l.sub.o) 24 requires less memory to store in output compressed data stream 20 than the literal of data string 14. In the LZ-2 type data compression technique as illustrated in FIG. 2, the LZ-2 data compression process searches for a data string in a table 30 that matches current input data string 14. If dictionary string 12 is detected, literal string 14 is then encoded in the output data stream by means of index i.sub.o and length l.sub.o, such as (i.sub., l.sub.o) 32, which points to the corresponding location of matching dictionary string 12 in dictionary 30.
Both LZ-1 or LZ-2 type compression technique can be designed to be either fixed or adaptive dictionary compression methods. In a fixed dictionary compression method, the "dictionary" (e.g., dictionary buffer 11 in the case of an LZ-1 fixed dictionary method, or table 30 in the case of an LZ-2 fixed dictionary method) typically comprises a set of fixed data entries, which is first loaded into the computer system's memory before compressing the input data stream. In an adaptive dictionary compression method, the "dictionary" (e.g., history buffer 11 or table 30) is modified to store new data strings into the dictionary during data compression process, if no matching data string is detected in the already stored data strings of the adaptive dictionary.
A fixed dictionary compression method provides efficient and good data compression performance when the set of input data in the input data stream correlates to the data entries in the fixed dictionary. However, where the input data stream comprises data that varies widely from one set of input data to another, the data compression performance of a fixed dictionary compression method typically decreases since the set of data entries in a fixed dictionary cannot be modified to accommodate such widely varying range of input data possibilities and the fixed dictionary is also typically limited by its memory allocation. An adaptive dictionary method provides the flexibility lacking in a fixed dictionary to accommodate a wide variety of input data. However, an adaptive dictionary method does not provide efficient data compression on small input data files, since an adaptive dictionary method typically does not begin to provide efficient compression performance until after having process about 1000 bytes of the input data stream.
It would therefore be desirable to provide an efficient data compression method that provides efficient data compression for data files generated by known software applications with a small file size, such as a file size of less than 1000 bytes of data.